"Tools or services for reporting and analytics for a Shopify store" matching MCP servers:

MCP server that connects AI assistants to Redash, enabling listing of assets, read-only query execution, dashboard inspection, and alert management through the Redash API.

A safety-gated Python MCP server for Metabase that lets MCP clients and agents inspect Metabase, run governed queries, and create or maintain dashboards, cards/questions, collections, snippets, permissions, and other Metabase assets through the Metabase REST API.

MCP server that allows Claude AI to interact directly with MySQL databases, enabling query execution and table information retrieval through natural language.

A production-grade MCP server for enterprise sales analytics, enabling LLM clients to query, analyze, and visualize sales data from a SQLite database through structured tools, resources, and prompts.

Enables exploring Microsoft Fabric / Power BI workspaces and semantic models, and executing ad-hoc DAX queries.

for shopify api interaction including product, customer, order

Enables interaction with Shopify store data via GraphQL API, providing tools for managing products, customers, orders, discounts, and more with robust error handling.

Enables interaction with Shopify store data via the GraphQL Admin API to manage products, customers, orders, and collections. Supports multi-store configurations and provides comprehensive management tools for e-commerce administration in both local and remote environments.

Enables AI assistants to access and manage Shopify store data including products, orders, inventory, and analytics through the Model Context Protocol. It allows users to query store performance and customer details using natural language.

Enables interaction with Shopify store data (products, customers, orders) via GraphQL, providing comprehensive tools for store management through Claude.

Enables AI applications to run SQL queries and retrieve results from Oracle Database.

A read-only DuckDB MCP server offering context-efficient analytics tools (list_datasets, describe_table, profile_column, explain, query) with a semantic layer for business rules, security guards, and disclosed truncation to help LLMs produce correct answers while minimizing token usage.

An MCP server for Snowflake that enables table discovery, metadata inspection, and SQL query execution through natural language, supporting password, key-pair, and OAuth authentication.

Provides a scalable knowledge graph implementation for Model Context Protocol using Elasticsearch, enabling AI models to store and query information with advanced search capabilities, memory-like behavior, and multi-zone architecture.

A local-only MCP server that uses SQLite to store, search, and manage a personal library of AI prompts. It enables developers to organize and reuse prompts across multiple AI clients like Claude and Cursor while keeping all data on their local machine.

Enables Claude to query a Postgres analytics schema via a read-only MCP server, with tools auto-generated from live database introspection and configurable SQL queries defined in YAML.

Universal Database MCP Server enabling AI assistants to connect and query multiple databases including Databricks, BigQuery, PostgreSQL, MySQL, SQL Server, SQLite, and MariaDB through a unified interface.

Enables AI agents to query a Shopify store's orders, products, and inventory levels read-only through the Admin GraphQL API, with no write capability and demo fixtures by default. Runs out of the box without credentials and paces calls on query cost.

OrionBelt Analytics is an MCP server that analyzes relational database schemas and generates RDF/OWL ontologies with embedded SQL mappings. It provides relationship-aware Text-to-SQL with automatic fan-trap prevention, GraphRAG for intelligent schema discovery, and interactive charting -- all accessible through any MCP-compatible AI client.

A standalone MCP server plus admin GUI for Couchbase Enterprise Analytics and Couchbase Capella Analytics, exposing 55 well-typed, audited tools for query execution, schema introspection, and cluster management.